---
title: "Pilot Data 2020"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    social: menu
    source_code: embed
    vertical_layout: scroll
    theme: spacelab
---

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(rio)
library(here)
library(colorblindr)
library(gghighlight)
library(forcats)
library(ggrepel)
library(gt)
library(knitr)
library(kableExtra)
library(reactable)
library(plotly)

opts_chunk$set(echo = FALSE,
               fig.width = 5,
               fig.height = 6)

theme_set(theme_minimal(base_size = 8))

outcome <- import(here("data", "client_data_outcome.sav"),
               setclass = "tbl_df") %>% 
  characterize() %>% 
  janitor::clean_names() 

rm_prge <- import(here("data", "repeated_measures_prge.sav"),
               setclass = "tbl_df") %>% 
  characterize() %>% 
  janitor::clean_names() 

head(outcome)
head(rm_prge)

rm_drkat <- import(here("data", "drkat_rm.csv"),
                   setclass = "tbl_df") %>% 
  janitor::clean_names()

head(rm_drkat)

brief_data <- import(here("data", "brief_pilot_data.xlsx"),
                     setclass = "tbl_df") %>% 
  janitor::clean_names()

head(brief_data)

falo_rm <- import(here("data", "falo_rm.xlsx"),
                  setclass = "tbl_df") %>% 
  janitor::clean_names()
```

# PRGE Outcome

Column {.tabset data-width=650}
-----------------------------------------------------------------------

```{r outcome measures data organization, include=FALSE}
head(outcome)

brief <- outcome %>% 
  filter(client == "PRGE") %>% 
  select(1, c(16:31))

brief_prge <- brief %>% 
  select(client, brief_eri_pre_self, brief_eri_post_self, brief_eri_pre_inf, brief_eri_post_inf)

brief_tidy <- brief_prge %>% 
  rename("Self Pre ERI" = brief_eri_pre_self,
         "Self Post ERI" = brief_eri_post_self,
         "Parent Pre ERI" = brief_eri_pre_inf,
         "Parent Post ERI" = brief_eri_post_inf) %>% 
  pivot_longer(
    cols = c(2:5),
    names_to = "measure",
    values_to = "score"
  )

prge_brief_parent <- brief_data %>% 
  filter(client == "PRGE") %>% 
  select(client, 8, 9, 16, 17) %>% 
  rename("SM Pre" = self_monitor_pre_parent,
         "SM Post" = self_monitor_post_parent,
         "EC Pre" = emotional_control_pre_parent,
         "EC Post" = emotional_control_post_parent) %>% 
  pivot_longer(
    cols = c(2:5),
    names_to = "measure",
    values_to = "score"
  )

prge_parent <- c("SM Pre",
         "SM Post",
         "EC Pre",
         "EC Post")

class <- outcome %>% 
  filter(client == "PRGE") %>% 
  select(client, class_total_pre, class_total_post) %>% 
  rename("Pre Score" = class_total_pre,
         "Post Score" = class_total_post)

class_tidy <- class %>% 
   pivot_longer(
    cols = c(2:3),
    names_to = "measure",
    values_to = "score"
  )


symptoms <- outcome %>% 
  filter(client == "PRGE") %>% 
  select(1, c(6:13)) %>% 
  rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
         "Feeling Slow Post" = pcss_post_feeling_slow,
         "Feeling Foggy Pre" = pcss_pre_feeling_foggy,
         "Feeling Foggy Post" = pcss_post_feeling_foggy,
         "Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
         "Difficulty Concentrating Post" = pcss_post_difficulty_concentrating, 
         "Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
         "Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>% 
  pivot_longer(
    cols = c(2:9),
    names_to = "measure",
    values_to = "score"
  )

hit <- outcome %>% 
  filter(client == "PRGE") %>% 
  select(client, hit_pre, hit_post) %>% 
  rename("Pre Score" = hit_pre,
         "Post Score" = hit_post) %>% 
   pivot_longer(
    cols = c(2:3),
    names_to = "measure",
    values_to = "score"
  )
```

```{r outcome plots, include=FALSE}
#geom_rect(aes(xmin = -Inf, xmax = Inf, ymin = 65, ymax = 100),
            #fill = "lightgreen") + #insert before geom_col 

prge_brief <- c("Self Pre ERI",
                "Self Post ERI",
                "Parent Pre ERI",
                "Parent Post ERI")
              
class_positions <- c("Pre Score", "Post Score")

pcss_positions <- c("Difficulty Remembering Post",
                    "Difficulty Remembering Pre",
                    "Difficulty Concentrating Post",
                     "Difficulty Concentrating Pre",
                     "Feeling Foggy Post",
                    "Feeling Foggy Pre",
                    "Feeling Slow Post",
                    "Feeling Slow Pre")

hit_positions <- c("Pre Score", "Post Score")

p1 <- ggplot(brief_tidy, aes(measure, score)) +
  geom_hline(yintercept = 65, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = prge_brief) +
  scale_y_continuous(limits = c(0, 100),
                     breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "T-score",
       title = "BRIEF Scores",
       subtitle = "Emotion Regulation Index",
       caption = "T-scores Above 65 are Clinically Significant") 

prge_parent_graph <- ggplot(prge_brief_parent, aes(measure, score)) +
  geom_hline(yintercept = 65, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = prge_parent) +
  scale_y_continuous(limits = c(0, 100),
                     breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "T-score",
       title = "BRIEF Scores",
       subtitle = "Parent Responses to the Self-Monitor and Emotional Control Scales",
       caption = "T-scores Above 65 are Clinically Significant") 

prge_parent_graph 
  
p1

p2 <- ggplot(class_tidy, aes(measure, score)) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = class_positions) +
  scale_y_continuous(limits = c(0, 60),
                     breaks = c(10, 20, 30, 40, 50, 60)) +
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "CLASS Scores") 
 p2


p3 <- ggplot(symptoms, aes(measure, score)) +
  geom_hline(yintercept = 30, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = pcss_positions) +
  scale_y_continuous(limits = c(0, 6),
                     breaks = c(0, 1, 2, 3, 4, 5, 6)) + 
  coord_flip() +
  geom_text(aes(measure, score, label = score),
            nudge_y = -0.5,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        plot.subtitle = element_text(color = "black", size = 10, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "PCSS Results",
       subtitle = "Cognitive Symptoms",
       caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms") 

p3

p3a <- ggplot(hit, aes(measure, score)) +
  geom_hline(yintercept = 50, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = hit_positions) +
  scale_y_continuous(limits = c(0, 60),
                     breaks = c(10, 20, 30, 40, 50, 60)) + 
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "HIT Results",
       caption = "Scores of 50 or Greater Suggest Headaches Impact Daily Functioning") 

p3a
```

### BRIEF Client-Parent Responses
```{r prge brief, include=TRUE}
p1

```

### BRIEF Parent Responses
```{r prge parent brief, include=TRUE}
prge_parent_graph
```

### CLASS
```{r prge class, include=TRUE}
p2
```


### PCSS

```{r prge pcss, include=TRUE}
p3
```


### HIT

```{r prge hit, include=TRUE}
p3a
```


Column {data-width=350}
-----------------------------------------------------------------------

### Client Demographics

```{r, include=FALSE}
head(outcome)

demo_prge <- outcome %>% 
  filter(client == "PRGE") %>% 
  select(2:5)
  
head(demo_prge)

prge_table <- demo_prge %>% 
  gt() %>% 
  cols_label(sex = "Sex",
             age = "Age",
             prev_mtbi = "Prior Concussions",
             hx_depression = "History of Depression or Anxiety") %>% 
  cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>% 
  tab_header(title = "Client Demographics")
  
prge_table
```

```{r prge table, include=TRUE}
prge_table
```

# PRGE Repeated 

Column {.tabset data-width=650}
-----------------------------------------------------------------------

### Status Tracking

```{r repeated measures data cleaning, include=FALSE}

head(rm_prge)

track <- rm_prge %>% 
  select(session, status)

p4 <- ggplot(track, aes(session, status)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 6),
                     breaks = c(1, 2, 3, 4, 5, 6)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Number of Times Required to Reread Content",
       title = "Status Tracking Goal") 

p4


effort_data <- rm_prge %>% 
  select(session, effort)

p5 <- ggplot(effort_data, aes(session, effort)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 5),
                     breaks = c(1, 2, 3, 4, 5)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Perceived Effort During Reading",
       title = "Perceived Effort While Reading",
       caption = "1 = No Effort\n 2 = A little Effort\n 3 = Somewhat Effortful\n 4 = Quite Effortful\n 5 = Extremely Effortful") 

p5

helpfulness <- rm_prge %>% 
  select(session, help)

p6 <- ggplot(helpfulness, aes(session, help)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 5),
                     breaks = c(1, 2, 3, 4, 5)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Perceived Helpfulness",
       title = "Perceived Helpfulness of Reading Strategies",
       caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful") 

p6
```


```{r status, include=TRUE}
p4
```

### Perceived Effort

```{r effort, include=TRUE, fig.align="left"}
p5
```

### Perceived Strategy Helpfulness 

```{r helpfulness, include=TRUE, fig.align="left"}
p6
```


# FALO Outcome

Column {.tabset data-width=650}
-----------------------------------------------------------------------

```{r falo measures data organization, include=FALSE}
head(outcome)

falo <- outcome %>% 
  filter(client == "FALO")

falo_brief_self <- brief_data %>% 
  filter(client == "FALO") %>% 
  select(client,
         working_memory_pre_self, 
         working_memory_post_self,
         plan_organize_pre_sr,
         plan_organize_post_sr,
         task_monitor_pre_sr,
         task_monitor_post_sr) %>% 
  rename("WM Pre" = working_memory_pre_self,
         "WM Post" = working_memory_post_self,
         "PO Pre" = plan_organize_pre_sr,
         "PO Post" = plan_organize_post_sr,
         "TM Pre" = task_monitor_pre_sr,
         "TM Post" = task_monitor_post_sr) %>% 
  pivot_longer(
    cols = c(2:7),
    names_to = "measure",
    values_to = "score"
  ) 


falo_sr_brief <- c("WM Pre",
         "WM Post",
         "PO Pre",
         "PO Post",
         "TM Pre",
         "TM Post")
  
falo_sr_plot <- ggplot(falo_brief_self, aes(measure, score)) +
  geom_hline(yintercept = 65, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = falo_sr_brief) +
  scale_y_continuous(limits = c(0, 100),
                     breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "T-score",
       title = "BRIEF Scores",
       subtitle = "Working Memory, Plan/Organize, and Task Monitoring Scales",
       caption = "T-scores Above 65 are Clinically Significant") 

falo_sr_plot


falo_brief_parent <- brief_data %>% 
  filter(client == "FALO") %>% 
  select(client,
         working_memory_pre_parent, 
         working_memory_post_parent,
         plan_organize_pre_parent,
         plan_organize_post_parent,
         task_monitor_pre_parent,
         task_monitor_post_parent) %>% 
  rename("WM Pre" = working_memory_pre_parent,
         "WM Post" = working_memory_post_parent,
         "PO Pre" = plan_organize_pre_parent,
         "PO Post" = plan_organize_post_parent,
         "TM Pre" = task_monitor_pre_parent,
         "TM Post" = task_monitor_post_parent) %>% 
  pivot_longer(
    cols = c(2:7),
    names_to = "measure",
    values_to = "score"
  ) 

falo_parent_plot <- ggplot(falo_brief_parent, aes(measure, score)) +
  geom_hline(yintercept = 65, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = falo_sr_brief) +
  scale_y_continuous(limits = c(0, 100),
                     breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "T-score",
       title = "BRIEF Scores",
       subtitle = "Working Memory, Plan/Organize, and Task Monitoring Scales",
       caption = "T-scores Above 65 are Clinically Significant") 

falo_parent_plot

class_falo <- falo %>% 
  select(client, class_total_pre, class_total_post) %>% 
  rename("Pre Score" = class_total_pre,
         "Post Score" = class_total_post) %>% 
   pivot_longer(
    cols = c(2:3),
    names_to = "measure",
    values_to = "score"
  )

pcss_falo <- falo %>% 
  select(1, c(6:13)) %>% 
  rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
         "Feeling Slow Post" = pcss_post_feeling_slow,
         "Feeling Foggy Pre" = pcss_pre_feeling_foggy,
         "Feeling Foggy Post" = pcss_post_feeling_foggy,
         "Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
         "Difficulty Concentrating Post" = pcss_post_difficulty_concentrating, 
         "Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
         "Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>% 
  pivot_longer(
    cols = c(2:9),
    names_to = "measure",
    values_to = "score"
  )

hit_falo <- falo %>% 
  select(client, hit_pre, hit_post) %>% 
  rename("Pre Score" = hit_pre,
         "Post Score" = hit_post) %>% 
   pivot_longer(
    cols = c(2:3),
    names_to = "measure",
    values_to = "score"
  )
```

```{r falo plots, include=FALSE}

p8 <- ggplot(class_falo, aes(measure, score)) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = class_positions) +
  scale_y_continuous(limits = c(0, 60),
                     breaks = c(10, 20, 30, 40, 50, 60)) +
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "CLASS Scores") 
 p8


p9 <- ggplot(pcss_falo, aes(measure, score)) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = pcss_positions) +
  scale_y_continuous(limits = c(0, 6),
                     breaks = c(0, 1, 2, 3, 4, 5, 6)) + 
  geom_text(aes(measure, score, label = score),
            nudge_y = -1,
            color = "white") +
  coord_flip() +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "PCSS Results",
       subtitle = "Cognitive Symptoms",
       caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms") 

p9

falo_pcss_table <- pcss_falo %>% 
  select(-client) %>% 
  gt() %>% 
  cols_label(measure = "PCSS Question",
             score = "Response") %>% 
  cols_align(align = "left", columns = vars(measure)) %>% 
  cols_align(align = "center", columns = vars(score)) %>% 
  tab_header(title = "PCSS Results",
             subtitle = "Cognitive Symptoms")

falo_pcss_table

falo_reactable <- pcss_falo %>% 
  select(-client) %>% 
  rename("PCSS Question" = measure,
         "Response" = score) %>% 
  reactable()

falo_reactable



p10 <- ggplot(hit_falo, aes(measure, score)) +
  geom_hline(yintercept = 50, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = hit_positions) +
  scale_y_continuous(limits = c(0, 60),
                     breaks = c(10, 20, 30, 40, 50, 60)) + 
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "HIT Results",
       caption = "Scores of 50 or Greater Suggest Headaches Significantly Impact Daily Functioning") 

p10
```

### BRIEF Self Report

```{r falo brief, include=TRUE, fig.width=6}
falo_sr_plot
```

### BRIEF Parent Report

```{r falo brief parent, include=TRUE, fig.width=6}
falo_parent_plot
```

### CLASS

```{r falo class, include=TRUE, fig.width=6}
p8
```

### PCSS

```{r falo pcss, include=TRUE}
falo_pcss_table
```

### HIT

```{r falo hit, include=TRUE}
p10
```

Column {data-width=350}
-----------------------------------------------------------------------

### Client Demographics

```{r, include=FALSE}
head(outcome)

demo_falo <- outcome %>% 
  filter(client == "FALO") %>% 
  select(2:5)
  
head(demo_falo)

falo_table <- demo_falo %>% 
  gt() %>% 
  cols_label(sex = "Sex",
             age = "Age",
             prev_mtbi = "Prior Concussions",
             hx_depression = "History of Depression or Anxiety") %>% 
  cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>% 
  tab_header(title = "Client Demographics")
  
falo_table
```

```{r falo table, include=TRUE}
falo_table
```

# FALO Repeated 

Column {.tabset data-width=650}
-----------------------------------------------------------------------

### Status Tracking 1

```{r falo repeated measures data cleaning, include=FALSE}

head(falo_rm)

falo_status_1 <- falo_rm %>% 
  select(session, status_1)

falo_status_1_plot <- ggplot(falo_status_1, aes(session, status_1)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 7),
                     breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Number of Nights Per Week Gone to Bed Prior to 3:00 AM",
       title = "Status Tracking Goal 1") 

falo_status_1_plot

phone_falo <- falo_rm %>% 
  select(session, num_nights)

phone_falo_graph <- ggplot(phone_falo, aes(session, num_nights)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 7),
                     breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Number of Nights Per Week Implementing No-Phone Strategy",
       title = "No Phone Strategy",
       subtitle = "To be implemented 1:00-7:00 AM") 

phone_falo_graph

falo_effect <- falo_rm %>% 
  select(session, effect)

falo_effect_graph <- ggplot(falo_effect, aes(session, effect)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 5),
                     breaks = c(1, 2, 3, 4, 5)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Perceived Effectiveness",
       title = "Perceived Effectiveness of No Phone Strategy",
       caption = "1 = Not Effective at All\n 2 = Not Effective\n 3 = Somewhat Effective\n 4 = Effective\n 5 = Very Effective") 

falo_effect_graph

falo_status_2 <- falo_rm %>% 
  select(session, status_2)

falo_status_2_plot <- ggplot(falo_status_2, aes(session, status_2)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 5),
                     breaks = c(0, 1, 2, 3, 4, 5)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Number of Missing Assignments per Week",
       title = "Status Tracking Goal 2") 

falo_status_2_plot

head(falo_rm)

falo_freq_1 <- falo_rm %>% 
  select(session, planner)

falo_freq_1_plot <- ggplot(falo_freq_1, aes(session, planner)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 10),
                     breaks = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Number of Weekly Assignments Entered into Calendar",
       title = "Frequency of Planner Use") 

falo_freq_1_plot

falo_help_1 <- falo_rm %>% 
  select(session, help_plan)

falo_planner_plot <- ggplot(falo_help_1, aes(session, help_plan)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 5),
                     breaks = c(1, 2, 3, 4, 5)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Perceived Helpfulness",
       title = "Perceived Helpfulness of Tracking Assignments in Planner",
       caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful") 

falo_planner_plot


falo_freq_2 <- falo_rm %>% 
  select(session, num_days)

falo_freq_2_plot <- ggplot(falo_freq_2, aes(session, num_days)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 7),
                     breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Number of Days Per Week Using Time Block Strategy",
       title = "Frequency of Time Block Strategy Use") 

falo_freq_2_plot

falo_help_2 <- falo_rm %>% 
  select(session, help_block)

falo_block_plot <- ggplot(falo_help_2, aes(session, help_block)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 5),
                     breaks = c(1, 2, 3, 4, 5)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Perceived Helpfulness",
       title = "Perceived Helpfulness of Time Block Strategy",
       caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful") 

falo_block_plot
```


```{r falo status 1, include=TRUE}
falo_status_1_plot
```

### Phone Strategy Use

```{r falo phone graph, include=TRUE, fig.align="left"}
phone_falo_graph
```

### Perceived Effectiveness 

```{r phone strategy helpfulness, include=TRUE, fig.align="left"}
falo_effect_graph
```

### Status Tracking 2

```{r falo status tracking 2, include=TRUE}
falo_status_2_plot
```

### Planner Use
```{r falo planner use, include=TRUE}
falo_freq_1_plot
```

### Planner Helpfulness
```{r falo planner helpfulness, include=TRUE}
falo_planner_plot
```

### Time Block Use
```{r falo time block use, include=TRUE}
falo_freq_2_plot
```

### Planner Helpfulness
```{r falo time block helpfulness, include=TRUE}
falo_block_plot
```


# DRKAT Outcome 

Column {.tabset data-width=650}
-----------------------------------------------------------------------

```{r drkat measures data organization, include=FALSE}
head(outcome)


drkat_brief_2 <- brief_data %>% 
  filter(client == "DRKAT") %>% 
  select(client, 22, 23) %>% 
  rename("Working Memory Pre" = working_memory_pre_self,
         "Working Memory Post" = working_memory_post_self) %>% 
  pivot_longer(
    cols = c(2:3),
    names_to = "measure",
    values_to = "score"
  )

drkat <- outcome %>% 
  filter(client == "DRKAT")

brief_drkat <- drkat %>% 
  select(1, 16, 17, 20, 21, 32, 33) %>% 
  rename("Pre Global" = brief_global_pre_self,
         "Post Global" = brief_global_post_self,
         "Pre BRI" = brief_bri_pre_self,
         "Post BRI" = brief_bri_post_self,
         "Pre MI" = brief_mi_pre_self,
         "Post MI" = brief_mi_post_self) %>% 
  pivot_longer(
    cols = c(2:7),
    names_to = "measure",
    values_to = "score"
  )

drkat_brief_graph <- c("Working Memory Pre", "Working Memory Post")

class_drkat <- drkat %>% 
  select(client, class_total_pre, class_total_post) %>% 
  rename("Pre Score" = class_total_pre,
         "Post Score" = class_total_post) %>% 
   pivot_longer(
    cols = c(2:3),
    names_to = "measure",
    values_to = "score"
  )


pcss_drkat <- drkat %>% 
  select(1, c(6:13)) %>% 
  rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
         "Feeling Slow Post" = pcss_post_feeling_slow,
         "Feeling Foggy Pre" = pcss_pre_feeling_foggy,
         "Feeling Foggy Post" = pcss_post_feeling_foggy,
         "Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
         "Difficulty Concentrating Post" = pcss_post_difficulty_concentrating, 
         "Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
         "Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>% 
  pivot_longer(
    cols = c(2:9),
    names_to = "measure",
    values_to = "score"
  )

hit_drkat <- drkat %>% 
  select(client, hit_pre, hit_post) %>% 
  rename("Pre Score" = hit_pre,
         "Post Score" = hit_post) %>% 
   pivot_longer(
    cols = c(2:3),
    names_to = "measure",
    values_to = "score"
  )
```

```{r drkat plots, include=FALSE}

drkat_brief_plot <- ggplot(drkat_brief_2, aes(measure, score)) +
  geom_hline(yintercept = 65, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = drkat_brief_graph) +
  scale_y_continuous(limits = c(0, 100),
                     breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "T-score",
       title = "BRIEF Scores",
       subtitle = "Working Memory Scale",
       caption = "T-scores Above 65 are Clinically Significant") 

drkat_brief_plot

drkat_class_plot <- ggplot(class_drkat, aes(measure, score)) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = class_positions) +
  scale_y_continuous(limits = c(0, 60),
                     breaks = c(10, 20, 30, 40, 50, 60)) +
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "CLASS Scores") 

drkat_class_plot


drkat_pcss_plot <- ggplot(pcss_drkat, aes(measure, score)) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = pcss_positions) +
  scale_y_continuous(limits = c(0, 6),
                     breaks = c(0, 1, 2, 3, 4, 5, 6)) + 
  geom_text(aes(measure, score, label = score),
            nudge_y = -1,
            color = "white") +
  coord_flip() +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "PCSS Results",
       subtitle = "Cognitive Symptoms",
       caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms") 

drkat_pcss_plot

drkat_hit_plot <- ggplot(hit_drkat, aes(measure, score)) +
  geom_hline(yintercept = 50, 
             linetype = "dashed",
             size = 1) +
  geom_col(fill = "blue", 
           alpha = 0.7) +
  scale_x_discrete(limits = hit_positions) +
  scale_y_continuous(limits = c(0, 60),
                     breaks = c(10, 20, 30, 40, 50, 60)) + 
  geom_text(aes(measure, score, label = score),
            nudge_y = -3,
            color = "white") +
  theme(panel.grid.major.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.x = element_line(color = "gray80")) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10),
        plot.caption = element_text(size = 10)) +
  labs(x = "",
       y = "Score",
       title = "HIT Results",
       caption = "Scores of 50 or Greater Suggest Headaches Significantly Impact Daily Functioning") 

drkat_hit_plot
```

### BRIEF 
```{r drkat brief, include=TRUE, fig.width=6}
drkat_brief_plot
```

### CLASS

```{r drkat class, include=TRUE, fig.width=6}
drkat_class_plot
```

### PCSS

```{r drkat pcss, include=TRUE}
drkat_pcss_plot
```

### HIT

```{r drkat hit, include=TRUE}
drkat_hit_plot
```

Column {data-width=350}
-----------------------------------------------------------------------

### Client Demographics

```{r, include=FALSE}
head(outcome)

demo_drkat <- outcome %>% 
  filter(client == "DRKAT") %>% 
  select(2:5)
  
head(demo_drkat)

drkat_table <- demo_drkat %>% 
  gt() %>% 
  cols_label(sex = "Sex",
             age = "Age",
             prev_mtbi = "Prior Concussions",
             hx_depression = "History of Depression or Anxiety") %>% 
  cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>% 
  tab_header(title = "Client Demographics")
  
drkat_table
```

```{r drkat table, include=TRUE}
drkat_table
```


# DRKAT Repeated

Column {.tabset data-width=650}
-----------------------------------------------------------------------

### Status Tracking

```{r repeated measures drkat data cleaning, include=FALSE}

drkat_track <- rm_drkat %>% 
  select(session, status)

drkat_status_plot <- ggplot(drkat_track, aes(session, status)) +
  geom_line() +
  geom_point(size = 2) +
  scale_x_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  scale_y_continuous(limits = c(0, 10),
                     breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
  theme_classic() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 10),
        axis.title=element_text(size=10),
        strip.text = element_text(size = 10)) +
  labs(x = "Session",
       y = "Number of House Chores Completed per Week",
       title = "Status Tracking Goal") 

drkat_status_plot


```


```{r drkat status, include=TRUE}
drkat_status_plot
```